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Thinking ahead for prep courses, if you only had time to take one, which would you think is more valuable for MFE prep?
Are there any good books or source material so I can get comfortable with the topic beforehand? I was a little surprised as well because it seemed PDEs we’re super important.Just wanted to add that I’ve taken the advanced calculus course, it’s good but I feel like mfe programs go over that in detail. Linear is not in my experience.
I only saw pde for stoc Calc 2 even then it wasn’t much. I assume you need pde’s more for pricing but I’m not really an expert there. I would saw coming in to any mfe know how to use pandas and numpy well and be good at basic maths.ie) linear, Calc,etcAre there any good books or source material so I can get comfortable with the topic beforehand? I was a little surprised as well because it seemed PDEs we’re super important.
Quantnet now offers an online Python course as well
We do have python notebooks where we do a lot of classes, but it’s not structured well in terms of setting up a work style project. I mean some people probably do, but the structure of our code wasn’t something that I would write when working for a job. In that sense it might be interesting to see how to write python code “professionally”. Maybe @Onegin can give his opinion on thisQuantnet now offers an online Python course as well
Would love to hear about the kind of Python projects you do at CMU and the level of knowledge expected there.
PDEs 'use' calculus.Are there any good books or source material so I can get comfortable with the topic beforehand? I was a little surprised as well because it seemed PDEs we’re super important.
Agree; we code a lot in python, but it’s typically subordinate to the topic under study. For example, write this simulation, ML Algo, Data science study, in python. The pro is the curriculum goes beyond the “recipe book” approach to ML / DS into the underlying theory, assumptions, and evolution.We do have python notebooks where we do a lot of classes, but it’s not structured well in terms of setting up a work style project. I mean some people probably do, but the structure of our code wasn’t something that I would write when working for a job. In that sense it might be interesting to see how to write python code “professionally”. Maybe @Onegin can give his opinion on this
This is 100% correct.Agree; we code a lot in python, but it’s typically subordinate to the topic under study. For example, write this simulation, ML Algo, Data science study, in python. The pro is the curriculum goes beyond the “recipe book” approach to ML / DS into the underlying theory, assumptions, and evolution.
That’s different from developing production quality code. I heard once (like on a podcast last week) that software development progressed from an individual caffeine fueled cowboy approach to a firm-wide cross team synchronized activity. So you have to think about versioning, inter-operability, standards, duplication of efforts, documentation, to name a few. That’s not covered, and is very important in a professional setting where you’re working on stuff that has a lot of financial risk. But, It’s not obvious to me that it could / should be covered in such a program. There are other ways to obtain that knowledge (C++ course here being one of them), but it’s harder to learn ML / StoCal at a high resolution without the focus of a masters program in my opinion. Of course, I’m probably one of the dimmer bulbs in the program, so take this w a grain of salt.
Whose the instructor or creator of the course??Quantnet now offers an online Python course as well
Would love to hear about the kind of Python projects you do at CMU and the level of knowledge expected there.
@APalley who is a current practitioner with years of industry experience. I'm sure you are familiar with his exceptional guidance as TA for the C++ courses.Whose the instructor or creator of the course??